Etleap ETL Platform
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An Etleap ETL Platform is an cloud-based ETL platform.
- Example(s):
- Counter-Example(s):
- See: Data Pipeline.
References
2021
- https://etleap.com/product/
- QUOTE: ... Create perfect data pipelines and cloud data warehouses from day one. ...
2021
- https://etleap.com/jobs/
- QUOTE: ... We started Etleap out of frustration with the exorbitant amounts of engineering work required to set up, maintain, and scale data pipelines for analytics. Our vision is to make it simple for analytics teams to quickly and securely connect the data sources that power their businesses. We’re doing this by removing all of the traditional complexities of data integration and creating a new kind of ETL that enables the end user of data to integrate and transform data from any source. …
2020
- (Stitchdata, 2020) ⇒ Stitchdata. (2020). "Etleap vs. Google Cloud Dataprep vs. Stitch - ETL software comparison."
- QUOTE: Most businesses have data stored in a variety of locations, from in-house databases to SaaS platforms. To get a full picture of their finances and operations, they pull data from all those sources into a data warehouse or data lake and run analytics against it. But they don't want to build and maintain their own data pipelines. Fortunately, it’s not necessary to code everything in-house. Here's an comparison of three such tools, head to head.
- Etleap is a cloud-based ETL platform.
- Google Cloud Dataprep is a data service for exploring, cleaning, and preparing structured and unstructured data. It's one of several Google data analytics services, including:
- Stitch Data Loader is a cloud-based platform for ETL — extract, transform, and load. ...
- …
Etleap supports transformation such as parsing, extracting, translating, and filtering in the data pipeline via a graphical interface.
- …
Etleap supports more than 50 data sources, including databases, cloud services, and file and event streams. Customers can request that the company build a new data source, but no one outside of the company can build new data sources or make improvements to existing sources. It supports Amazon Redshift and S3 and Snowflake destinations.
- QUOTE: Most businesses have data stored in a variety of locations, from in-house databases to SaaS platforms. To get a full picture of their finances and operations, they pull data from all those sources into a data warehouse or data lake and run analytics against it. But they don't want to build and maintain their own data pipelines. Fortunately, it’s not necessary to code everything in-house. Here's an comparison of three such tools, head to head.